R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(77.7,78.89,90.2,77.26,80.76,84.93,66.08,71.56,80.78,83.31,85.3,73.94,78.7,81.32,86.8,80.76,84.46,84.21,73.64,70.85,83.78,89.12,78.93,80.54,81.67,82.53,88.2,89.17,83.7,89.79,77.58,70.11,88.07,92.49,83.33,90.05,82.91,88.52,96.42,90.87,86.4,97.47,85.67,79.91,95.73,94.6,91.92,90.38,82.31,87.82,101.29,89.58,87.83,99.95,82.67,84.65,97.83,97.47,97.66,99.14,90.02,100.97,112.48,91.44,108.46,98.41,89.35,92.8,100.43,104.85,108.36,101.54,105.26,101.8,112.36,99.5,104.65,101.13,89.8,87.84,96.41,103.26,100.31,92.33,96.19,96.37,103.06,101.5,101.88,100.85,95.56,87.6,101.18,110.8,101.1,104.42,103.27,100.87,107.8,104.99,100.76,104.46,100.62,87.84,107.31,115.61,103.43,109.93,104.43,106.69,123.1,109.42,101.46,124.48,101.49,100.46,115.51,113.37,115.4,118.2,106.82,110.17,119.91,112.31,110.62,120.37,97.94,103.02,116.36,108.51,122.54,121.32,112.25,109.89,129.58,107.2,118.68,118.25,102.67,104.19,117.74,123.3,122.2,112.71,118.53,115.32,127.36,110.45,122.22,123.39,116.2,109.22,116.98,132.89,125.24,115.68)
> par1 = '12'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as.numeric(par1)
> (n <- length(x))
[1] 156
> (np <- floor(n / par1))
[1] 13
> arr <- array(NA,dim=c(par1,np))
> j <- 0
> k <- 1
> for (i in 1:(np*par1))
+ {
+ j = j + 1
+ arr[j,k] <- x[i]
+ if (j == par1) {
+ j = 0
+ k=k+1
+ }
+ }
> arr
       [,1]  [,2]  [,3]  [,4]   [,5]   [,6]   [,7]   [,8]   [,9]  [,10]  [,11]
 [1,] 77.70 78.70 81.67 82.91  82.31  90.02 105.26  96.19 103.27 104.43 106.82
 [2,] 78.89 81.32 82.53 88.52  87.82 100.97 101.80  96.37 100.87 106.69 110.17
 [3,] 90.20 86.80 88.20 96.42 101.29 112.48 112.36 103.06 107.80 123.10 119.91
 [4,] 77.26 80.76 89.17 90.87  89.58  91.44  99.50 101.50 104.99 109.42 112.31
 [5,] 80.76 84.46 83.70 86.40  87.83 108.46 104.65 101.88 100.76 101.46 110.62
 [6,] 84.93 84.21 89.79 97.47  99.95  98.41 101.13 100.85 104.46 124.48 120.37
 [7,] 66.08 73.64 77.58 85.67  82.67  89.35  89.80  95.56 100.62 101.49  97.94
 [8,] 71.56 70.85 70.11 79.91  84.65  92.80  87.84  87.60  87.84 100.46 103.02
 [9,] 80.78 83.78 88.07 95.73  97.83 100.43  96.41 101.18 107.31 115.51 116.36
[10,] 83.31 89.12 92.49 94.60  97.47 104.85 103.26 110.80 115.61 113.37 108.51
[11,] 85.30 78.93 83.33 91.92  97.66 108.36 100.31 101.10 103.43 115.40 122.54
[12,] 73.94 80.54 90.05 90.38  99.14 101.54  92.33 104.42 109.93 118.20 121.32
       [,12]  [,13]
 [1,] 112.25 118.53
 [2,] 109.89 115.32
 [3,] 129.58 127.36
 [4,] 107.20 110.45
 [5,] 118.68 122.22
 [6,] 118.25 123.39
 [7,] 102.67 116.20
 [8,] 104.19 109.22
 [9,] 117.74 116.98
[10,] 123.30 132.89
[11,] 122.20 125.24
[12,] 112.71 115.68
> arr.mean <- array(NA,dim=np)
> arr.sd <- array(NA,dim=np)
> arr.range <- array(NA,dim=np)
> for (j in 1:np)
+ {
+ arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
+ arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
+ arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
+ }
> arr.mean
 [1]  79.22583  81.09250  84.72417  90.06667  92.35000  99.92583  99.55417
 [8] 100.04250 103.90750 111.16750 112.49083 114.88833 119.45667
> arr.sd
 [1] 6.586062 5.192778 6.318261 5.572009 7.202568 7.774259 6.998621 5.687260
 [9] 6.675358 8.430041 7.800836 8.165409 6.969768
> arr.range
 [1] 24.12 18.27 22.38 17.56 18.98 23.13 24.52 23.20 27.77 24.02 24.60 26.91
[13] 23.67
> (lm1 <- lm(arr.sd~arr.mean))

Call:
lm(formula = arr.sd ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
    1.79976      0.05119  

> (lnlm1 <- lm(log(arr.sd)~log(arr.mean)))

Call:
lm(formula = log(arr.sd) ~ log(arr.mean))

Coefficients:
  (Intercept)  log(arr.mean)  
      -1.4756         0.7395  

> (lm2 <- lm(arr.range~arr.mean))

Call:
lm(formula = arr.range ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
     9.5227       0.1360  

> postscript(file="/var/www/html/rcomp/tmp/123oz1229009408.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2ery71229009408.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Section',header=TRUE)
> a<-table.element(a,'Mean',header=TRUE)
> a<-table.element(a,'Standard Deviation',header=TRUE)
> a<-table.element(a,'Range',header=TRUE)
> a<-table.row.end(a)
> for (j in 1:np) {
+ a<-table.row.start(a)
+ a<-table.element(a,j,header=TRUE)
+ a<-table.element(a,arr.mean[j])
+ a<-table.element(a,arr.sd[j] )
+ a<-table.element(a,arr.range[j] )
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/3uohv1229009408.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4swo21229009408.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Lambda',header=TRUE)
> a<-table.element(a,1-lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5uls81229009408.tab") 
> 
> system("convert tmp/123oz1229009408.ps tmp/123oz1229009408.png")
> system("convert tmp/2ery71229009408.ps tmp/2ery71229009408.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.537   0.307   0.634